Objective:
1. Discover and validate diagnostic biomarkers that predict, diagnose, and/or distinguish apple postharvest physiological disorders (Scientific objective).
2. Compile sets of biomarkers that could be used to predict, diagnose, or distinguish apple postharvest browning disorders and test their efficacy by classifying/reclassifying browning disorders based on new metabolic/genetic information (Scientific and outreach objective).
3. Estimate the economic impact (both benefits and costs) to the apple industry of utilizing biomarker-based diagnostic tools to manage apple postharvest physiological disorders (Scientific and outreach objective).
4. Activly facilitate transfer of new biomarker-based technology for immediate implementation using current platforms and development of new tailored platforms utilizing biomarker-based technology (outreach objective).

Approach:
Conduct an advisory panel, industry, and academic query that will assess current needs, scope, and understanding of diagnosis and non-chemical management of postharvest browing disorders, representing a variety of similar disorders occurring in multiple economically important cultivars, have been selected for this study. Employ experimental strategies that utilize susceptible cultivars along with chemical and cultural controls that both control the selected disorders while accentuating metabolic differences and differences in gene expression between healthy apples and disorder-prone apples. Comprehensive metabolic and gene-expression profiling will be employed to discover disorder-specific diagnostic biochemical and genetic biomarkers. Metabolic and gene-expression evaluations will be screened by the bioinformatics cooperators. Metabolic and gene expression profiles will be statistically modeled and mined by statistics/modeling cooperator to determine disorder-related metabolic changes and select biomarkers that bestpredict whether an apple will develop a certain disorder of differential that disorder from others. Biomarkers associated with individual disorder will be compiled and compared to select those that will be the bases of discrimination of postharvest browing disorders. An economic study will validate cost-effectiveness biomarker-based management strategies and platforms. New tools will be used to classify or re-classify disorders using the new metabolic information. Diagnostic/prediction biomarkers and tools will be presented to fruit producers, retailers, and agricultural service companies in extension, industry, and scientific meeting to determine the best means for pilot testing and implementation of this new storage management and quality assurance technology.